Battery Cell Modeling and Online Estimation of State of Charge of Lithium-ion Battery

Battery models are vital for the development of electric vehicles. It helps stimulate and predict the voltage response of the battery, which can ensure the efficiency of other control algorithms and maintain the safe usage of the battery. In the first part of this thesis, MATLAB® is used to build a battery model of battery cell. The battery model considers the influences of magnitude of discharge current and state of charge on the parameters of the battery model. It can predict the voltage response within 4 % of voltage error under dynamic load. In the second part of this thesis, a model-based Kalman filter is adopted for state of charge estimation. This algorithm is confirmed to have good estimation efficiency. It can converge and overcome the problem of wrong initial point of state of charge within 60 seconds.